These proceedings gather selected papers from the 9th International Conference on Green Intelligent Transportation Systems and Safety, held in Guilin, China on July 1-3, 2018. They feature cutting-edge studies on Green Intelligent Mobility Systems, the guiding motto being to achieve “green, intelligent, and safe transportation systems.” The contributions presented here can help promote the development of green mobility and intelligent transportation technologies to improve interconnectivity, resource sharing, flexibility and efficiency. Given its scope, the book will benefit researchers and engineers in the fields of Transportation Technology and Traffic Engineering, Automotive and Mechanical Engineering, Industrial and System Engineering, and Electrical Engineering alike.

Health Economics and Financing Encapsulates different case studies where green-IOT and machine learning can be used for making significant progress towards improvising the quality of life and sustainable environment. The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier. Green Internet of Things and Machine Learning lays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare. Audience The book will be helpful for research scholars and researchers in the fields of computer science and engineering, information technology, electronics and electrical engineering. Industry experts, particularly in R&D divisions, can use this book as their problem-solving guide.

In a world where most international trade is carried by sea, each port can be seen as a unique chokepoint competing to attract ever more traffic and economic activities. However, ports can also be seen as parts of a wider system, which can be defined as a system of two or more ports located in proximity within a given area. Their fate and governance is jointly influenced when belonging to the same region, country, or transnational space. Investments, shocks, innovations, and delays occurring in one port often affect other ports within a certain spatial range and time lapse. Further understanding of such co-developments in port systems is necessary to go beyond local specificities, through a multidisciplinary and multi-level contribution. Port Systems in Global Competition is an answer to the strong and urgent need for reviewing the relevant theories, concepts, methods, and sources that can be mobilized for the analysis of port systems. With contributions from reputable scholars coming from no less than 11 countries in Europe, Asia, and North America, this book delves into the analysis of port systems from diverse disciplinary angles (geography, regional science, economics, management, engineering, and mathematics/computer sciences), and covering innovative empirical approaches to various port systems in the world. The theoretical and empirical knowledge can support and enhance decision-making in relation with the development of ports, supply chains, and transport networks in general. This book is an ideal companion to academics and upper-level students interested in the analysis of transport and economic systems in general, as well as the effective ways to answer complex issues in transportation and socio-economic development. It will be a valuable resource for those researching or studying transportation and supply chains, maritime and port economics, as well as regional development and human geography.

This book focuses on open issues of Society 5.0, a new paradigm of a society that balances a human-centred approach and technologies based on cyber-physical systems and artificial intelligence. The book contains results of how intelligent or cyber-physical systems help to improve the quality of life in society despite new challenges. Discusses implemented breakthrough systems, models, programs, and methods that cover the following topics: biomedicine and healthcare, innovations in socio-economic systems, intelligent energetics, advances in transport systems, human-centric technologies. These approaches help to improve human society using cyber-physical systems in a dramatically changing environment. The target audience of the book are practitioners, enterprises representatives, scientists, PhD and Master students who perform scientific research on the application of cyber-physical systems towards Society 5.0.

Innovative and smart mobility systems are expected to make transportation systems more sustainable, inclusive, and safe. Because of changing mobility paradigms, transport planning and design require different methodological approaches. Over twelve chapters, this book examines and analyzes Mobility as a Service (MaaS), travel behavior, traffic control, intelligent transportation system design, electric, connected, and automated vehicles, and much more.

Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision. Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.

This book presents the trends, challenges, and advances in Internet of Things (IoT) in the areas of industrial management and industrial engineering. The authors look at how smart environments (smart city, smart university, smart regions, smart transportation, etc.) affect the way industrial management and industrial engineering are envisioned, planned, and applied and how engineers must incorporate new ideas and methods now and in the future. Some topics include the impact of ICT on the emergency response vehicle driving time, car accident detecting systems based on machine learning algorithms, smart city platforms based on citizen reporting services, and IoT-based household energy consumption prediction using machine learning. The book brings together contributions from academics and practitioners from around the world to discuss the intersection of IoT, industry and management.